WHAT DO VARS TELL US ABOUT THE IMPACT OF A CREDIT SUPPLY SHOCK?
通过蒙特卡洛实验评估多种结构VAR模型识别信贷供给冲击的表现，发现最佳模型估计出信贷供给冲击使利差上升10个基点会导致一年后GDP增长和通胀下降1%，且这类冲击在大衰退期间解释了约一半的GDP增长下降。
Abstract In the aftermath of the recent financial crisis, a variety of structural vector autoregression (VAR) models have been proposed to identify credit supply shocks. Using a Monte Carlo experiment, we show that the performance of these models can vary substantially, with some identification schemes producing particularly misleading results. When applied to U.S. data, the estimates from the best performing VAR models indicate, on average, that credit supply shocks that raise spreads by 10 basis points reduce GDP growth and inflation by 1% after one year. These shocks were important during the Great Recession, accounting for about half the decline in GDP growth.